Advances In Robot Learning

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Recent Advances In Robot Learning

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Author : Judy A. Franklin
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Recent Advances In Robot Learning written by Judy A. Franklin and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.

Recent Advances in Robot Learning contains seven papers on robot learning written by leading researchers in the field. As the selection of papers illustrates, the field of robot learning is both active and diverse. A variety of machine learning methods, ranging from inductive logic programming to reinforcement learning, is being applied to many subproblems in robot perception and control, often with objectives as diverse as parameter calibration and concept formulation. While no unified robot learning framework has yet emerged to cover the variety of problems and approaches described in these papers and other publications, a clear set of shared issues underlies many robot learning problems. Machine learning, when applied to robotics, is situated: it is embedded into a real-world system that tightly integrates perception, decision making and execution. Since robot learning involves decision making, there is an inherent active learning issue. Robotic domains are usually complex, yet the expense of using actual robotic hardware often prohibits the collection of large amounts of training data. Most robotic systems are real-time systems. Decisions must be made within critical or practical time constraints. These characteristics present challenges and constraints to the learning system. Since these characteristics are shared by other important real-world application domains, robotics is a highly attractive area for research on machine learning. On the other hand, machine learning is also highly attractive to robotics. There is a great variety of open problems in robotics that defy a static, hand-coded solution. Recent Advances in Robot Learning is an edited volume of peer-reviewed original research comprising seven invited contributions by leading researchers. This research work has also been published as a special issue of Machine Learning (Volume 23, Numbers 2 and 3).

Robot Intelligence

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Author : Honghai Liu
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-08-05

Robot Intelligence written by Honghai Liu and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-08-05 with Computers categories.

Robot intelligence has become a major focus of intelligent robotics. Recent innovation in computational intelligence including fuzzy learning, neural networks, evolutionary computation and classical Artificial Intelligence provides sufficient theoretical and experimental foundations for enabling robots to undertake a variety of tasks with reasonable performance. This book reflects the recent advances in the field from an advanced knowledge processing perspective; there have been attempts to solve knowledge based information explosion constraints by integrating computational intelligence in the robotics context.

Robotics In Education

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Author : Wilfried Lepuschitz
language : en
Publisher: Springer
Release Date : 2018-09-01

Robotics In Education written by Wilfried Lepuschitz and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-01 with Computers categories.

This proceedings volume comprises the latest achievements in research and development in educational robotics presented at the 9th International Conference on Robotics in Education (RiE) held in Qawra, St. Paul's Bay, Malta, during April 18-20, 2018. Researchers and educators will find valuable methodologies and tools for robotics in education that encourage learning in the fields of science, technology, engineering, arts and mathematics (STEAM) through the design, creation and programming of tangible artifacts for creating personally meaningful objects and addressing real-world societal needs. This also involves the introduction of technologies ranging from robotics platforms to programming environments and languages. Extensive evaluation results are presented that highlight the impact of robotics on the students’ interests and competence development. The presented approaches cover the whole educative range from elementary school to the university level in both formal as well as informal settings.

Advances In Robot Control

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Author : Sadao Kawamura
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-07-17

Advances In Robot Control written by Sadao Kawamura and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-07-17 with Technology & Engineering categories.

Robotics is still a young science, but we can already identify the people who de?ned its primary course of development. Suguru Arimoto is one of them. His early works laid the foundations of what nowadays is called modern robot control, and we believe it is both appropriate and necessary to write a book on recent advances in this ?eld in the context of his scienti?c interests. While presenting recent advances in robot control is the main intention of this book, we also think it is appropriate to highlight Suguru Arimoto’s research career, main scienti?c achievements, and his personality, too. This can be very inspiring and instructive, especially for young researchers. What are the most remarkable features of Suguru Arimoto? On the p- sonal side, his vitality is striking. He is always focused on a research target, and it is always a fun and a pleasure to discuss with him scienti?c pr- lems and to learn from him. His passion to explain things that might not appear obvious is endless. It is very encouraging to younger researchers that, at this stage of his career, he is still a very active, approachable, and in?u- tial researcher, and a person who leads by example. On the scienti?c side, we should stress his research philosophy. He believes that the ?nal result should be simple and have a clear physical (or physiological, in his recent research) interpretation.

Advances In Robot Learning

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Author : Jeremy Wyatt
language : en
Publisher: Springer Science & Business Media
Release Date : 2000-10-11

Advances In Robot Learning written by Jeremy Wyatt and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-10-11 with Computers categories.

This book constitutes the thoroughly refereed post-workshop proceedings of the 8th European Workshop on Learning Robots, EWLR'99, held in Lausanne, Switzerland in September 1999. The seven revised full workshop papers presented were carefully reviewed and selected for inclusion in the book. Also included are two invited full papers. Among the topics addressed are map building for robot navigation, multi-task reinforcement learning, neural network approaches, example-based learning, situated agents, planning maps for mobile robots, path finding, autonomous robots, and biologically inspired approaches.

Recent Advances In Robot Learning From Demonstration

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Author : Harish Ravichandar
language : en
Publisher:
Release Date : 2020

Recent Advances In Robot Learning From Demonstration written by Harish Ravichandar and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.

In the context of robotics and automation, learning from demonstration (LfD) is the paradigm in which robots acquire new skills by learning to imitate an expert. The choice of LfD over other robot learning methods is compelling when ideal behavior can be neither easily scripted (as is done in traditional robot programming) nor easily defined as an optimization problem, but can be demonstrated. While there have been multiple surveys of this field in the past, there is a need for a new one given the considerable growth in the number of publications in recent years. This review aims to provide an overview of the collection of machine-learning methods used to enable a robot to learn from and imitate a teacher. We focus on recent advancements in the field and present an updated taxonomy and characterization of existing methods. We also discuss mature and emerging application areas for LfD and highlight the significant challenges that remain to be overcome both in theory and in practice.

Learning For Adaptive And Reactive Robot Control

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Author : Aude Billard
language : en
Publisher: MIT Press
Release Date : 2022-02-08

Learning For Adaptive And Reactive Robot Control written by Aude Billard and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-08 with Technology & Engineering categories.

Methods by which robots can learn control laws that enable real-time reactivity using dynamical systems; with applications and exercises. This book presents a wealth of machine learning techniques to make the control of robots more flexible and safe when interacting with humans. It introduces a set of control laws that enable reactivity using dynamical systems, a widely used method for solving motion-planning problems in robotics. These control approaches can replan in milliseconds to adapt to new environmental constraints and offer safe and compliant control of forces in contact. The techniques offer theoretical advantages, including convergence to a goal, non-penetration of obstacles, and passivity. The coverage of learning begins with low-level control parameters and progresses to higher-level competencies composed of combinations of skills. Learning for Adaptive and Reactive Robot Control is designed for graduate-level courses in robotics, with chapters that proceed from fundamentals to more advanced content. Techniques covered include learning from demonstration, optimization, and reinforcement learning, and using dynamical systems in learning control laws, trajectory planning, and methods for compliant and force control . Features for teaching in each chapter: applications, which range from arm manipulators to whole-body control of humanoid robots; pencil-and-paper and programming exercises; lecture videos, slides, and MATLAB code examples available on the author’s website . an eTextbook platform website offering protected material[EPS2] for instructors including solutions.

Robot Learning

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Author : J. H. Connell
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Robot Learning written by J. H. Connell and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Technology & Engineering categories.

Building a robot that learns to perform a task has been acknowledged as one of the major challenges facing artificial intelligence. Self-improving robots would relieve humans from much of the drudgery of programming and would potentially allow operation in environments that were changeable or only partially known. Progress towards this goal would also make fundamental contributions to artificial intelligence by furthering our understanding of how to successfully integrate disparate abilities such as perception, planning, learning and action. Although its roots can be traced back to the late fifties, the area of robot learning has lately seen a resurgence of interest. The flurry of interest in robot learning has partly been fueled by exciting new work in the areas of reinforcement earning, behavior-based architectures, genetic algorithms, neural networks and the study of artificial life. Robot Learning gives an overview of some of the current research projects in robot learning being carried out at leading universities and research laboratories in the United States. The main research directions in robot learning covered in this book include: reinforcement learning, behavior-based architectures, neural networks, map learning, action models, navigation and guided exploration.

Artificial Intelligence For Future Generation Robotics

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Author : Rabindra Nath Shaw
language : en
Publisher: Elsevier
Release Date : 2021-06-19

Artificial Intelligence For Future Generation Robotics written by Rabindra Nath Shaw and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-19 with Technology & Engineering categories.

Artificial Intelligence for Future Generation Robotics offers a vision for potential future robotics applications for AI technologies. Each chapter includes theory and mathematics to stimulate novel research directions based on the state-of-the-art in AI and smart robotics. Organized by application into ten chapters, this book offers a practical tool for researchers and engineers looking for new avenues and use-cases that combine AI with smart robotics. As we witness exponential growth in automation and the rapid advancement of underpinning technologies, such as ubiquitous computing, sensing, intelligent data processing, mobile computing and context aware applications, this book is an ideal resource for future innovation. - Brings AI and smart robotics into imaginative, technically-informed dialogue - Integrates fundamentals with real-world applications - Presents potential applications for AI in smart robotics by use-case - Gives detailed theory and mathematical calculations for each application - Stimulates new thinking and research in applying AI to robotics

Autonomous Robotics And Deep Learning

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Author : Vishnu Nath
language : en
Publisher: Springer
Release Date : 2014-04-25

Autonomous Robotics And Deep Learning written by Vishnu Nath and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-04-25 with Computers categories.

This Springer Brief examines the combination of computer vision techniques and machine learning algorithms necessary for humanoid robots to develop “true consciousness.” It illustrates the critical first step towards reaching “deep learning,” long considered the holy grail for machine learning scientists worldwide. Using the example of the iCub, a humanoid robot which learns to solve 3D mazes, the book explores the challenges to create a robot that can perceive its own surroundings. Rather than relying solely on human programming, the robot uses physical touch to develop a neural map of its environment and learns to change the environment for its own benefit. These techniques allow the iCub to accurately solve any maze, if a solution exists, within a few iterations. With clear analysis of the iCub experiments and its results, this Springer Brief is ideal for advanced level students, researchers and professionals focused on computer vision, AI and machine learning.